MATLAB PROJECT
Content-Aware
Enhancement of Images With Filamentous Structures
Abstract:
In this paper, we describe a novel enhancement method for images
containing filamentous structures. Our method combines a gradient sparsity
constraint with a filamentous structure constraint for the effective removal of
clutter and noise from the background. The method is applied and evaluated on
three types of data: 1) confocal microscopy images of neurons; 2) calcium
imaging data; and 3) images of road pavement. We found that the images enhanced
by our method preserve both the structure and the intensity details of the
original object. In the case of neuron microscopy, we find that the neurons
enhanced by our method are better correlated with the original structure
intensities than the neurons enhanced by well-known vessel enhancement methods.
Experiments on simulated calcium imaging data indicate that both the number of
detected neurons and the accuracy of the derived calcium activity are improved.
Applying our method to real calcium data, more regions exhibiting calcium
activity in the full field of view were found. In road pavement crack
detection, smaller or milder cracks were detected after using our enhancement
method.
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